基于VMD-DBN的滚动轴承故障诊断方法

doi:10.12068/j.issn.1005-3026.2021.08.007

东北大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (8): 1105-1110.DOI: 10.12068/j.issn.1005-3026.2021.08.007

基于VMD-DBN的滚动轴承故障诊断方法

任朝晖，于天壮，丁东，周世华

(东北大学机械工程与自动化学院，辽宁沈阳110819)

修回日期:2020-10-20 接受日期:2020-10-20 发布日期:2021-09-02
通讯作者: 任朝晖
作者简介:任朝晖 (1968-)，男，辽宁沈阳人，东北大学教授，博士生导师.
基金资助:
中央高校基本科研业务费专项资金资助项目(N180304018).

Fault Diagnosis Method of Rolling Bearing Based on VMD-DBN

REN Zhao-hui， YU Tian-zhuang， DING Dong， ZHOU Shi-hua

School of Mechanical Engineering & Automation， Northeastern University， Shenyang 110819， China.

Revised:2020-10-20 Accepted:2020-10-20 Published:2021-09-02
Contact: REN Zhao-hui
About author:-
Supported by:
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摘要/Abstract

摘要： 为揭示滚动轴承故障振动信号的典型特征规律，结合变分模态分解(VMD)与深度置信网络(DBN)的优势，提出轴承振动信号特征的提取方法.将信号先进行基于VMD的分解，根据各模态分量频谱图确定其模态参数，得到若干个模态分量.然后，基于DBN强大的特征提取能力，采用DBN无监督特征提取方法，将得到的模态分量映射到一维，并融合各分量的DBN特征形成特征向量，将其作为粒子群优化支持向量机(PSO-SVM)的输入进行故障诊断.实验验证与对比分析证明了VMD-DBN方法的可行性与优越性.

关键词: 滚动轴承；变分模态分解；深度置信网络；特征提取；故障诊断

Abstract: In order to identify the vibration signal features of faulty bearing， a feature extraction method of bearing vibration signals based on the variational mode decomposition (VMD) and deep belief network (DBN) is proposed. First， the signal is decomposed based on VMD and the parameters of each modal component are determined by the modal component spectrogram， thus several modal components being obtained. Then an unsupervised feature extraction method based on DBN， which has powerful feature extraction ability， is used to map the modal components obtained to one dimension， and the DBN features of each component are merged to form feature vectors and input into particle swarm optimization support vector machine (PSO-SVM) for fault diagnosis. Experimental verification and comparative analysis show the feasibility and superiority of the VMD-DBN method proposed.

Key words: rolling bearing; VMD(variational mode decomposition); DBN(deep belief network); feature extraction; fault diagnosis

中图分类号:

TH165.3

任朝晖，于天壮，丁东，周世华. 基于VMD-DBN的滚动轴承故障诊断方法[J]. 东北大学学报（自然科学版）, 2021, 42(8): 1105-1110.

REN Zhao-hui， YU Tian-zhuang， DING Dong， ZHOU Shi-hua. Fault Diagnosis Method of Rolling Bearing Based on VMD-DBN[J]. Journal of Northeastern University(Natural Science), 2021, 42(8): 1105-1110.

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基于VMD-DBN的滚动轴承故障诊断方法

Fault Diagnosis Method of Rolling Bearing Based on VMD-DBN

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